US 12,378,879 B2
Methods for predicting formation properties
Dung T. Phan, Brookshire, TX (US); Chao Liu, Brookshire, TX (US); and Younane N. Abousleiman, Norman, OK (US)
Assigned to SAUDI ARABIAN OIL COMPANY, Dhahran (SA)
Filed by ARAMCO SERVICES COMPANY, Houston, TX (US)
Filed on Mar. 28, 2022, as Appl. No. 17/656,814.
Prior Publication US 2023/0304397 A1, Sep. 28, 2023
Int. Cl. E21B 49/00 (2006.01); E21B 49/02 (2006.01); G06F 30/20 (2020.01)
CPC E21B 49/005 (2013.01) [E21B 49/02 (2013.01); G06F 30/20 (2020.01); E21B 2200/20 (2020.05)] 16 Claims
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1. A method for predicting a formation property of a formation, comprising the steps of:
drilling a first well that penetrates the formation,
obtaining well properties from the first well,
determining a measured formation property from the first well,
determining a correlation function that estimates a predicted formation property from the well properties, wherein the correlation function comprises coefficients,
calibrating the correlation function by modifying the coefficients until the predicted formation property best matches the measured formation property,
drilling a second well that penetrates the formation,
obtaining well properties from the second well,
determining the formation property from the second well by applying the correlation function with the modified coefficients to the well properties,
using, by a wellbore stability model, the formation property to plan an optimal well trajectory of the second well,
using the formation property to plan a mud program that minimizes instabilities of the second well;
using the formation property to recommend an optimal lost circulation material (LCM) blend to mitigate mud loss in the second well, and
drilling the second well,
wherein the coefficients for k correlation functions are modified by the following steps:
determining a coefficient adjustment vector for k well property vectors,
outputting k predicted formation properties by the correlation function,

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determining k measured formation properties corresponding to the k well property vectors, and
adjusting the coefficient vector such that the adjusted coefficients yields the optimal predicted formation property that best matches the measured formation property.